Clay detection and quantification using low frequency electromagnetic measurements

Abstract

Methods and systems are provided for clay detection, clay typing, and clay volume quantification using electromagnetic measurements on a porous media sample at a low frequency less than 5000 Hz. The electromagnetic measurements are used to determine and store permittivity data that characterizes permittivity of the porous media sample at the low frequency less than 5000 Hz. The low frequency electromagnetic measurements can be performed in a laboratory, at a wellsite or other surface location. The low frequency electromagnetic measurements are nondestructive, and the results indicate that the methods and systems are highly sensitive to the existence of clays.

What is claimed is: 
     
       1. A method for characterizing clay content of a porous media sample, the method comprising:
 i) conducting an electromagnetic measurement on the porous media sample at a low frequency less than 5000 Hz, wherein the electromagnetic measurement is used to determine and store permittivity data that characterizes permittivity of the porous media sample at the low frequency less than 5000 Hz; 
 ii) extracting a parameter from the permittivity data that characterizes permittivity of the porous media sample at the low frequency less than 5000 Hz; and 
 iii) using the parameter extracted from the permittivity data in ii) as input to a computational model, wherein the computational model relates the parameter extracted from the permittivity data in ii) to data that characterizes at least one clay type and corresponding clay volume fraction for the porous media sample, wherein the operations of i), ii), and iii) are performed at a surface location. 
 
     
     
       2. The method according to  claim 1 , further comprising:
 storing or outputting the data that characterizes at least one clay type and corresponding clay volume fraction for the porous media sample as provided by the computational model in iii). 
 
     
     
       3. The method according to  claim 1 , wherein:
 the computational model of iii) is derived by measuring permittivity of porous media of different known clay types and different clay volume fractions at the low frequency less than 5000 Hz and correlating a parameter extracted from the resultant permittivity to data that characterizes at least one clay type and corresponding clay volume fraction. 
 
     
     
       4. The method according to  claim 1 , wherein:
 the computational model of iii) is derived by measuring permittivity of porous media of different known clay types and different clay volume fractions at multiple low frequencies less than 5000 Hz and correlating a parameter extracted from the resultant permittivity to data that characterizes at least one clay type and corresponding clay volume fraction. 
 
     
     
       5. The method according to  claim 1 , wherein:
 the computational model of iii) relates a parameter extracted from measurement of permittivity of porous media at multiple low frequencies less than 5000 Hz to data that characterizes at least one clay type and corresponding clay volume fraction; and 
 the permittivity data of i) as well as the parameter extracted from the permittivity data in ii) are derived from electromagnetic measurements on the porous media sample at the multiple low frequencies less than 5000 Hz. 
 
     
     
       6. The method according to  claim 5 , wherein:
 the multiple low frequencies less than 5000 Hz comprises at least three frequencies less than or equal to 100 Hz. 
 
     
     
       7. The method according to  claim 5 , wherein:
 the multiple low frequencies less than 5000 Hz comprises a set of at least three frequencies between 100 Hz and 1 Hz. 
 
     
     
       8. The method according to  claim 1 , wherein:
 the parameter extracted from the permittivity data in ii) and input to the computational model of iii) is selected from the group consisting of: a frequency-specific slope, a frequency-specific permittivity, a critical frequency where the measurement of permittivity of the porous media sample diverges from permittivity of porous media that does not have clay, and combinations thereof. 
 
     
     
       9. The method according to  claim 1 , wherein:
 the permittivity data of i) represents relative permittivity or effective permittivity of the porous media sample. 
 
     
     
       10. The method according to  claim 1 , wherein:
 the permittivity data of i) is derived from a quadrature component of a measurement of complex conductivity of the porous media sample. 
 
     
     
       11. The method according to  claim 1 , wherein:
 the at least one clay type is selected from the group consisting of: kaolinite, smectite, illite, chlorite, and combinations thereof. 
 
     
     
       12. The method according to  claim 1 , wherein:
 the porous media sample comprises a formation rock sample. 
 
     
     
       13. The method according to  claim 12 , further comprising:
 using the data that characterizes at least one clay type and corresponding clay volume fraction as output from the computational model in iii) to calculate a value of cation exchange capacity (CEC) for the formation rock sample. 
 
     
     
       14. The method according to  claim 12 , further comprising:
 using the data that characterizes at least one clay type and corresponding clay volume fraction as output from the computational model in iii) for evaluation of a hydrocarbon reservoir corresponding to the formation rock sample. 
 
     
     
       15. The method according to  claim 1 , wherein:
 the extracting of the parameter in ii) is performed by a processor, or the computational model of iii) is embodied by a processor. 
 
     
     
       16. The method according to  claim 1 , wherein:
 the surface location is selected from the group consisting of: a laboratory, a wellsite or other surface location. 
 
     
     
       17. The method according to  claim 1 , wherein conducting the electromagnetic measurement on the porous media sample comprises:
 detecting an electromagnetic response signal with one or more receiver antennas, wherein phase-lock detection and amplification of the response signal is used to determine an amplitude and a phase of one or more voltage levels detected by the one or more receiver antennas; and 
 recording and processing the amplitude and phase of the one or more voltage levels to obtain a measurement of a complex conductivity (a) of the porous media, wherein the permittivity data in i) comprises the complex conductivity (a), and wherein the parameter extracted from the permittivity data that characterizes the permittivity of the porous media sample in ii) is extracted from a quadrature component of the complex conductivity. 
 
     
     
       18. A system for characterizing clay content of a porous media sample, the system comprising:
 at least one receiver antenna that, when performing at least one electromagnetic measurement at a low frequency less than 5000 Hz on the porous media sample, is configured to detect at least one electromagnetic response signal of the porous media sample; and 
 at least one processor that, when executing program instructions stored in memory, is configured to: 
 i) build or provide a computational model that relates a parameter extracted from measurement of permittivity of porous media at the low frequency less than 5000 Hz to data that characterizes at least one clay type and corresponding clay volume fraction; 
 ii) obtain permittivity data that characterizes permittivity of the porous media sample at the low frequency less than 5000 Hz, wherein the permittivity data is derived from the at least one electromagnetic response signal of the porous media; 
 iii) extract a parameter from the permittivity data that characterizes permittivity of the porous media sample at the low frequency less than 5000 Hz; and 
 iv) use the parameter extracted from the permittivity data in iii) as input to the computational model of i), wherein the computational model outputs data that characterizes at least one clay type and corresponding clay volume fraction for the porous media sample, 
 wherein the system is located at a surface location. 
 
     
     
       19. The system according to  claim 18 , wherein:
 the at least one processor is further configured to store or output the data that characterizes at least one clay type and corresponding clay volume fraction for the porous media sample as provided by the computational model in iv). 
 
     
     
       20. The system according to  claim 18 , wherein:
 the computational model of i) is derived by measuring permittivity of porous media of different known clay types and different clay volume fractions at the low frequency less than 5000 Hz and correlating a parameter extracted from the resultant permittivity to data that characterizes at least one clay type and corresponding clay volume fraction. 
 
     
     
       21. The system according to  claim 18 , wherein:
 the computational model of i) is derived by measuring permittivity of porous media of different known clay types and different clay volume fractions at multiple low frequencies less than 5000 Hz and correlating a parameter extracted from the resultant permittivity to data that characterizes at least one clay type and corresponding clay volume fraction. 
 
     
     
       22. The system according to  claim 18 , wherein:
 the computational model of i) relates a parameter extracted from measurement of permittivity of porous media at multiple low frequencies less than 5000 Hz to data that characterizes at least one clay type and corresponding clay volume fraction; and 
 the permittivity data obtained in ii) as well as the parameter extracted from the permittivity data in iii) are derived from electromagnetic measurements performed on the porous media sample at the multiple low frequencies less than 5000 Hz. 
 
     
     
       23. The system according to  claim 22 , wherein:
 the multiple low frequencies less than 5000 Hz comprises at least three frequencies less than or equal to 100 Hz. 
 
     
     
       24. The system according to  claim 22 , wherein:
 the multiple low frequencies less than 5000 Hz comprises a set of at least three frequencies between 100 Hz and 1 Hz.